ABSTRACT
We propose a hybrid architecture of wired and wireless sensors for smart fabric with applications including body dynamics and shape monitoring and patient rehabilitation. Our system is capable of acquiring data from up to 200 on-body sensors with 50Hz sampling rate using conventional low-cost hardware. The sensing and data processing is done in real time and the results available on a smaptphone, tablet or pc in 3D visual form or as alerts. The user experience of the demo will include trying out smart clothing that is enabled with the shape sensing fabric and observing the body shape dynamics on-screen in real time.
- Barry Dworkin, Neal E Miller, Susan Dworkin, Niels Birbaumer, Michael L Brines, Saran Jonas, Edwards P Schwentker, and Jacob J Graham. Behavioral method for the treatment of idiopathic scoliosis. Proceedings of the National Academy of Sciences, 82(8): 2493--2497, 1985.Google ScholarCross Ref
- Manuel D Rigo, Mónica Villagrasa, and Dino Gallo. A specific scoliosis classification correlating with brace treatment: description and reliability. Scoliosis, 5(1): 1, 2010.Google ScholarCross Ref
- Henk J Luinge and Peter H Veltink. Inclination measurement of human movement using a 3-d accelerometer with autocalibration. Neural Systems and Rehabilitation Engineering, IEEE Transactions on, 12(1): 112--121, 2004.Google Scholar
- Christina Goodvin, Edward J Park, Kevin Huang, and Kelly Sakaki. Development of a real-time three-dimensional spinal motion measurement system for clinical practice. Medical and Biological Engineering and Computing, 44(12): 1061--1075, 2006.Google ScholarCross Ref
- Wai-Yin Wong and Man-Sang Wong. Measurement of postural change in trunk movements using three sensor modules. Instrumentation and Measurement, IEEE Transactions on, 58(8): 2737--2742, 2009.Google Scholar
Index Terms
- Wearable sensor grid architecture for body posture and surface detection and rehabilitation
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